Does the Stock Market Overreact?
Abstract
Research in experimental psychology suggests that, in violation of Bayes' rule, most people tend to “overreact” to unexpected and dramatic news events. This study of market efficiency investigates whether such behavior affects stock prices. The empirical evidence, based on CRSP monthly return data, is consistent with the overreaction hypothesis. Substantial weak form market inefficiencies are discovered. The results also shed new light on the January returns earned by prior “winners” and “losers.” Portfolios of losers experience exceptionally large January returns as late as five years after portfolio formation.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Persistent evidence of irrationality has been identified, such as overreaction and the disposition effect.
“However, persistent evidence of irrationality has been identified, such as overreaction (Bondt & Thaler, 1985) and the disposition effect (Dhar & Zhu, 2006; Grinblatt & Keloharju, 2001; Shefrin & Statman, 1985).”
From Bridging the divide in financial market forecasting: machine learners vs. financial economists (2016) · cites this paper as Bondt & Thaler, 1985
Cited by
Sorted by citations
Maps of Bounded Rationality: Psychology for Behavioral Economics
Kahneman, D. (2003) · American Economic Review · doi:10.1257/000282803322655392 · Cited by 5,377 · see citing works
FAMA, E. F. (1991) · The Journal of Finance · doi:10.1111/j.1540-6261.1991.tb04636.x · Cited by 5,350 · see citing works
Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors
Barber, B. M., & Odean, T. (2000) · The Journal of Finance · doi:10.1111/0022-1082.00226 · Cited by 3,955 · see citing works
“Clinical versus Actuarial Judgment.”
Dawes, R. M., Faust, D., & Meehl, P. E. (1989) · Science · doi:10.1126/science.2648573 · Cited by 2,298 · see citing works
Simple technical trading rules and the stochastic properties of stock returns
BROCK, W., LAKONISHOK, J., & LeBARON, B. (1992) · The Journal of Finance · doi:10.1111/j.1540-6261.1992.tb04681.x · Cited by 2,301 · see citing works
… and the Cross-Section of Expected Returns
Harvey, C. R., Liu, Y., & Zhu, H. (2016) · Review of Financial Studies · doi:10.1093/rfs/hhv059 · Cited by 2,119 · see citing works
The Efficient Market Hypothesis and Its Critics
Malkiel, B. G. (2003) · Journal of Economic Perspectives · doi:10.1257/089533003321164958 · Cited by 2,161 · see citing works
From efficient markets theory to behavioral finance
Shiller, R. J. (2003) · Journal of Economic Perspectives · doi:10.1257/089533003321164967 · Cited by 1,835 · see citing works
Support theory: a nonextensional representation of subjective probability
Tversky, A., & Koehler, D. J. (1994) · Psychological Review · doi:10.1037/0033-295x.101.4.547 · Cited by 1,167 · see citing works
Chong, E., Han, C., & Park, F. C. (2017) · Expert Systems with Applications · doi:10.1016/j.eswa.2017.04.030 · Cited by 834 · see citing works
Behavioral Economics: Past, Present, and Future
Thaler, R. H. (2016) · American Economic Review · doi:10.1257/aer.106.7.1577 · Cited by 799 · see citing works
Self-citationDunning, D., Meyerowitz, J. A., & Holzberg, A. D. (1989) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.57.6.1082 · Cited by 758 · see citing works
Dissecting Characteristics Nonparametrically
Freyberger, J., Neuhierl, A., & Weber, M. (2020) · The Review of Financial Studies · doi:10.1093/rfs/hhz123 · Cited by 619 · see citing works
The Cross-section of Expected Stock Returns
Lewellen, J. (2015) · Critical Finance Review · doi:10.1561/104.00000024 · Cited by 407 · see citing works
How rewarding is technical analysis? Evidence from Singapore stock market
Wong, W.-K., Manzur, M., & Chew, B.-K. (2003) · Applied Financial Economics · doi:10.1080/0960310022000020906 · Cited by 236 · see citing works
Bridging the divide in financial market forecasting: machine learners vs. financial economists
Hsu, M.-W., Lessmann, S., Sung, M.-C., Ma, T., & Johnson, J. E. V. (2016) · Expert Systems with Applications · doi:10.1016/j.eswa.2016.05.033 · Cited by 195 · see citing works
A trend factor: any economic gains from using information over investment horizons?
Han, Y., Zhou, G., & Zhu, Y. (2016) · Journal of Financial Economics · doi:10.1016/j.jfineco.2016.01.029 · Cited by 202 · see citing works
Berthet, V. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.802439 · Cited by 191 · see citing works
Non-fungible tokens (NFTs): A review of pricing determinants, applications and opportunities
Kräussl, R., & Tugnetti, A. (2024) · Journal of Economic Surveys · doi:10.1111/joes.12597 · Cited by 96 · see citing works
News or Noise? The Stock Market Reaction to Different Types of Company-Specific News Events
Sprenger, T. O., & Welpe, I. M. (2011) · SSRN Electronic Journal · doi:10.2139/ssrn.1734632 · Cited by 28 · see citing works
Unpacking leverage and lagged effects: do digitally mature and complex firms outpace their rivals?
Daruwala, Z., Khan, F., & Ullah Jan, S. (2025) · Cogent Economics & Finance · doi:10.1080/23322039.2025.2577909 · Cited by 1 · see citing works
Informational Efficiency and Behaviour Within In-Play Prediction Markets
Angelini, G., De Angelis, L., & Singleton, C. (2020) · Social Science Research Network · doi:10.2139/ssrn.3505287
- Authors
- De BONDT, W. F. M., & THALER, R.
- Affiliations
- University of Wisconsin–Madison (US)
- ORCID
- THALER, RICHARD
- Venue
- The Journal of Finance
- Publisher
- Wiley
- Published
- 1985-07
- Volume
- 40
- Issue
- 3
- Pages
- 793-805
- ISSN
- 0022-1082 (ISSN-L)
- 1540-6261
- OpenAlex
- W2144487825
- Cited by
- 7,578
- References
- 0
- Citations by year
- 2026: 238 · 2025: 246 · 2024: 307 · 2023: 291 · 2022: 279 · 2021: 341 · 2020: 354 · 2019: 315 · 2018: 315 · 2017: 293 · 2016: 314 · 2015: 334 · 2014: 392 · 2013: 296 · 2012: 327
- FWCI
- 54.54
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Journal of Finance (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Markets and Investment Strategies
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Risk and Volatility Modeling
- Social Sciences › Decision Sciences › Management Science and Operations Research › Stock Market Forecasting Methods
- Keywords
- stock market overreaction, market efficiency, Bayes' theorem, investor behavior, January effect, winner and loser portfolios, stock returns, behavioral finance
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review